Summary

This project provides an MCP (Model Context Protocol) server designed to expose Strands Agents documentation to GenAI tools. It enables AI coding assistants to intelligently search and retrieve relevant documentation, facilitating "vibe-coding" of Strands Agents. The target audience includes developers leveraging AI assistants for agent development.

How It Works

The MCP server provides a model-driven approach by indexing curated documentation from llms.txt files. It features smart document search powered by TF-IDF with Markdown-aware scoring that prioritizes titles, headers, and code blocks. The system employs on-demand fetching, loading full document content only when necessary for performance. It also generates contextual snippets with relevance scoring and supports real HTTPS URLs.

Quick Start & Requirements

• Prerequisites: uv (install via official instructions) and Node.js (for npx).
• Installation: Configure your preferred MCP client (e.g., Kiro, Amazon Q, Claude Code, Cursor, VS Code) using provided JSON or command-line examples. The server command is typically uvx strands-agents-mcp-server.
• Testing: Use the MCP Inspector: npx @modelcontextprotocol/inspector uvx strands-agents-mcp-server (published) or npx @modelcontextprotocol/inspector python -m strands_mcp_server.
• Links: GitHub repository: https://github.com/strands-agents/mcp-server.

Highlighted Details

• Smart Document Search: TF-IDF with Markdown-aware scoring (titles, headers, code blocks).
• Curated Content: Indexes documentation from llms.txt files.
• On-Demand Fetching: Lazy-loads full document content.
• Snippet Generation: Provides contextual snippets with relevance scoring.
• Broad Integration: Compatible with 40+ MCP-supporting applications.

Maintenance & Community

The project includes a Contributing Guide and Code of Conduct. Specific details regarding core contributors, sponsorships, roadmap, or community channels (e.g., Discord, Slack) are not detailed in the provided README.

Licensing & Compatibility

• License: Apache License 2.0.
• Compatibility: The Apache 2.0 license is permissive, generally allowing commercial use and integration into closed-source projects.

Limitations & Caveats

The README does not explicitly detail limitations, alpha status, or known bugs. Setup requires specific tooling (uv, Node.js), and performance relies on the quality and structure of the indexed llms.txt documentation files.